Autonomous Model Context Protocol (MCP) engine for factual consistency, version reconciliation, and conflict resolution across engineering knowledge bases.
Autonomous Cross-Source Inconsistency & Contradiction Intelligence Engine for AI Agents
Problem • Capabilities • Limitations • Architecture • Quickstart • Tools Reference • Tutorials • Docs • License
Project Status: Active Development (v0.2.1)
Contradiction MCP is currently under active development. Core multi-format document ingestion (Markdown, RFC822 .eml, OpenXML .docx, and JSON) and cross-document contradiction discovery are operational and verified. Heuristic classifiers, deep JSON scoping, and public APIs are actively evolving prior to v1.0.0.
Modern engineering ecosystems rely on fragmented, uncoordinated sources of truth:
- Code Repositories: package.json, Dockerfile, CI/CD workflows (.github/workflows/.yml) - Deployment Manifests: Kubernetes YAML, Helm values, cloud environment configurations - Technical Documentation: Architecture guides, runbooks, developer setup portals, READMEs - Public Endpoints: OpenAPI/Swagger schemas, status feeds, live web documentation
When these systems diverge—for example, a Kubernetes manifest deploying Node.js 22 while technical documentation instructs developers to run Node.js 18, or conflicting database engine versions across staging and production—silent regressions, deploy failures, and hallucinations in LLM reasoning occur.
Contradiction MCP bridges these silos through automated multi-source ingestion, context-aware contradiction reasoning, source authority and freshness scoring, human-in-the-loop review/resolution workflows, and immutable audit trails.
From the project README.
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